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Combining spatial metabolomics and proteomics profiling of single cells

Nature Reviews Immunology volume 24, page 701 (2024)Cite this article

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Traditional mass spectrometry techniques are incredibly useful for multi-omics studies, as they can detect thousands of metabolites, such as lipids, peptides, proteins and glycans, in a single experiment without labeling, but they lack spatial information. Recent advances in mass spectrometry imaging have made it possible to perform spatial profiling of proteins and metabolites1. Despite this, analysing single-cell metabolomics with intracellular proteins remains difficult. To address this, our team combined two leading technologies, imaging mass cytometry (to study proteins) and time-of-flight secondary ion mass spectrometry (to study metabolites), and called this the single-cell spatially resolved metabolic (scSpaMet) framework2. Multi-parameter proteomics solves the challenges of single-cell phenotyping and segmentation, while spatial metabolomics reveals the cell-specific metabolic profiles in the tissue context. Using scSpaMet, we were able to simultaneously profile 25 protein markers and 200 metabolites in several tissue models, including tumour biopsies (for example, human lung cancer), lymphoid tissues (for example, tonsil samples) and endometrial tissues. scSpaMet revealed previously unknown chemical interactions between single cells. We also devised a companion data-integration algorithm to combine the proteomic and metabolic features of the native human tissues in situ.

How can spatially resolved proteomic and metabolic analyses of human tissues help elucidate health and disease better? As one example, cancer cells have altered metabolic needs to meet their rapid growth. Our study demonstrated that cancer cells indeed showed elevated glycolysis and aberrant cholesterol depletion2. In contrast, stromal regions showed greater deposition of cholesterol fragments than cancer cells. This suggests that the cancer cells are using up cholesterol as they rapidly proliferate. scSpaMet also showed that cancer cells and immune cells compete for shared metabolic resources on the basis of their proximity to blood vessels or endothelial cells. Understanding patient-specific spatial metabolic alterations in the tumour microenvironment could lead to more personalized cancer treatments.

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References

  1. Ganesh, S. et al. Spatially resolved 3D metabolomic profiling in tissues. Sci. Adv. 7, eabd0957 (2021).

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  2. Hu, T. et al. Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology. Nat. Commun. 14, 8260 (2023).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Authors and Affiliations

  1. Georgia Institute of Technology, Atlanta, GA, USA

    Mayar Allam & Ahmet F. Coskun

  2. Emory University, Atlanta, GA, USA

    Mayar Allam & Ahmet F. Coskun

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  1. Mayar Allam
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  2. Ahmet F. Coskun
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Correspondence to Ahmet F. Coskun.

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The authors declare no competing interests.

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Allam, M., Coskun, A.F. Combining spatial metabolomics and proteomics profiling of single cells. Nat Rev Immunol 24, 701 (2024). https://doi.org/10.1038/s41577-024-01084-8

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